susi

Python package for unsupervised and supervised self-organizing maps (SOM)


Keywords
data-science, machine-learning, opensource, python, self-organizing-map, semi-supervised-learning, som, supervised-learning, unsupervised-learning
License
BSD-3-Clause
Install
pip install susi==1.0.6

Documentation

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SUSI: SUpervised Self-organIzing maps in Python

Python package for unsupervised and supervised self-organizing maps (SOM)

Description

We present the SUSI package for Python. It includes a fully functional SOM for unsupervised and supervised tasks. The class structure is set up as follows:

  • SOMClustering: Unsupervised SOM for clustering
    • SOMEstimator: Base class for supervised SOMs
      • SOMRegressor: Regression SOM
      • SOMClassifier: Classification SOM
License: 3-Clause BSD license
Author: Felix M. Riese
Citation: see Citation and in the bibtex file
Documentation: Documentation
Installation: Installation guidelines
Paper: arXiv:1903.11114

Installation

pip install susi

More information can be found in the installation guidelines.

Examples

A collection of code examples can be found in the documentation. Code examples as Jupyter Notebooks can be found here:

Citation

The bibtex file including both references is available here.

Paper:

Felix M. Riese and S. Keller, "SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python", arXiv:1903.11114, 2019. Submitted to an ISPRS conference.

@article{riesekeller2019susi,
    author = {Riese, Felix~M. and Keller, Sina},
    title = {SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python},
    year = {2019},
    archivePrefix = {arXiv},
    eprint = {1903.11114},
    primaryClass = {cs.LG},
    url = {https://arxiv.org/abs/1903.11114}
}

Code:

Felix M. Riese, "SUSI: SUpervised Self-organIzing maps in Python", 10.5281/zenodo.2609130, 2019.

@misc{riese2019susicode,
    author = {Riese, Felix~M.},
    title = {{SUSI: SUpervised Self-organIzing maps in Python}},
    year = {2019},
    DOI = {10.5281/zenodo.2609130},
    publisher = {Zenodo},
    howpublished = {\href{https://doi.org/10.5281/zenodo.2609130}{doi.org/10.5281/zenodo.2609130}}
}